Climate adaptation game design to foster transdisciplinary and intercultural collaboration

Abstract. Addressing the complex challenges of climate adaptation requires transdisciplinary collaboration that bridges diverse knowledge systems across cultural and disciplinary boundaries. This paper presents insights from the "Climate Action Transdisciplinarity in Education and Research" (CATER) project, which implements game co-creation as an educational tool to foster transdisciplinary and transcultural collaboration on climate adaptation. Through annual schools, participants from diverse scientific, professional, and cultural backgrounds engage in an immersive learning process that integrates theoretical lectures, field visits, and collaborative game design. Participants develop games addressing real-world climate adaptation issues, including agricultural resilience, probabilistic forecast communication, and resource conflicts, thereby translating complex concepts into immersive, educational applications. In this paper we reflect on the co-creative process as it took place during two schools in 2023 (Kenya) and 2024 (Tanzania), and discuss game co-creation as boundary work, how it facilitates mutual learning and applies soft skills, while participants negotiate power dynamics, knowledge integration, and group facilitation challenges. A complementary evaluation using Q-methodology assessed changes in participants' perspectives on transdisciplinarity and co-production, revealing a shift from disciplinary viewpoints toward greater appreciation of collaborative, inclusive approaches in climate adaptation strategies. The findings highlight game design as an effective medium for experiential learning and transdisciplinary boundary work, although challenges remain regarding power imbalances, language barriers, and group dynamics. Importantly, the combination of game co-creation and systematic evaluation with Q-methodology offers a promising approach to enhance and assess transdisciplinary collaboration. Future CATER schools will allow us to refine these methods.